class_docstr: Random augment with fixed magnitude.
class_docstr_tok: ["Random","augment","with","fixed","magnitude","."]
code: def _quantize(self):
      if self.magnitude is not None:
          return tf.convert_to_tensor(self.magnitude)
      if self.quantum is None:
          return tf.random.uniform(shape=[], dtype=tf.float32)
      else:
          level = tf.random.uniform(
              shape=[], maxval=self.quantum + 1, dtype=tf.int32
          )
          return tf.cast(level, tf.float32) / self.quantum
  
file_path: objax/examples/fixmatch/libml/augment/randaugment/randaugment.py
imports: from typing import Optional
  import tensorflow
  from examples.fixmatch.libml.augment.randaugment import augment_ops
label_desc: Use image node_id 2 for calling the RandAugment obj's underlying member method code with example usage: obj._quantize() and returns: tf, tf, unknown